scholarly journals Fast Total Variation Method Based on Iterative Reweighted Norm for Airborne Scanning Radar Super-Resolution Imaging

2020 ◽  
Vol 12 (18) ◽  
pp. 2877
Author(s):  
Xingyu Tuo ◽  
Yin Zhang ◽  
Yulin Huang ◽  
Jianyu Yang
Keyword(s):  
Total Variation ◽  
Structural Characteristics ◽  
Super Resolution ◽  
Variation Method ◽  
High Dimensional ◽  
Imaging Method ◽  
Lp Norm ◽  
L2 Norm ◽  
The Matrix ◽  
Resolution Imaging

The total variation (TV) method has been applied to realizing airborne scanning radar super-resolution imaging while maintaining the outline of the target. The iterative reweighted norm (IRN) approach is an algorithm for addressing the minimum Lp norm problem by solving a sequence of minimum weighted L2 norm problems, and has been applied to solving the TV norm. However, during the solving process, the IRN method is required to update the weight term and result term in each iteration, involving multiplications and the inversion of large matrices. Consequently, it suffers from a huge calculation load, which seriously restricts the application of the TV imaging method. In this work, by analyzing the structural characteristics of the matrix involved in iteration, an efficient method based on suitable matrix blocking is proposed. It transforms multiplications and the inversion of large matrices into the computation of multiple small matrices, thereby accelerating the algorithm. The proposed method, called IRN-FTV method, is more time economical than the IRN-TV method, especially for high dimensional observation scenarios. Numerical results illustrate that the proposed IRN-FTV method enjoys preferable computational efficiency without performance degradation.

scholarly journals Airborne Radar Super-Resolution Imaging Based on Fast Total Variation Method

2021 ◽  
Vol 13 (4) ◽  
pp. 549
Author(s):  
Qiping Zhang ◽  
Yin Zhang ◽  
Yongchao Zhang ◽  
Yulin Huang ◽  
Jianyu Yang
Keyword(s):  
Computational Complexity ◽  
Total Variation ◽  
Super Resolution ◽  
Real Data ◽  
Radar Imaging ◽  
Matrix Inversion ◽  
Variation Method ◽  
Airborne Radar ◽  
The Matrix ◽  
Very High

Total variation (TV) is an effective super-resolution method to improve the azimuth resolution and preserve the contour information of the target in airborne radar imaging. However, the computational complexity is very high because of the matrix inversion, reaching O(N3). In this paper, a Gohberg–Semencul (GS) representation based fast TV (GSFTV) method is proposed to make up for the shortcoming. The proposed GSFTV method fist utilizes a one-dimensional TV norm as the regular term under regularization framework, which is conducive to achieve super-resolution while preserving the target contour. Then, aiming at the very high computational complexity caused by matrix inversion when minimizing the TV regularization problem, we use the low displacement rank feature of Toeplitz matrix to achieve fast inversion through GS representation. This reduces the computational complexity from O(N3) to O(N2), benefiting efficiency improvement for airborne radar imaging. Finally, the simulation and real data processing results demonstrate that the proposed GSFTV method can simultaneously improve the resolution and preserve the target contour. Moreover, the very high computational efficiency of the proposed GSFTV method is tested by hardware platform.

SAR Super-Resolution Imaging Method Based on Spectral Estimation

2017 ◽  
pp. 445-490
Author(s):  
Ruliang Yang ◽  
Haiying Li ◽  
Shiqiang Li ◽  
Ping Zhang ◽  
Lulu Tan ◽  
...  
Keyword(s):  
Spectral Estimation ◽  
Super Resolution ◽  
Imaging Method ◽  
Resolution Imaging

scholarly journals Adaptive Diagonal Total-Variation Generative Adversarial Network for Super-Resolution Imaging

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 57517-57526
Author(s):  
Zhang San-You ◽  
Cheng De-Qiang ◽  
Jiang Dai-Hong ◽  
Kou Qi-Qi ◽  
Ma Lu
Keyword(s):  
Total Variation ◽  
Super Resolution ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Resolution Imaging

scholarly journals Dynamic Supramolecular Interaction in Cucurbit[7]uril Host-Guest Complex Enables Autonomous Single Molecule Blinking and Super-Resolution Imaging in Cells and Tissues

2018 ◽  
Author(s):  
Ranjan Sasmal ◽  
Nilanjana Das Saha ◽  
Florian Schueder ◽  
Divyesh Joshi ◽  
Vasu Sheeba ◽  
...  
Keyword(s):  
Single Molecule ◽  
Guest Molecule ◽  
Noncovalent Interactions ◽  
Super Resolution ◽  
Imaging Method ◽  
Supramolecular Interaction ◽  
Guest Molecules ◽  
Host Guest Complex ◽  
Resolution Imaging ◽  
2D And 3D

Synthetic supramolecular host-guest complexes are inherently dynamic as they employ weak and reversible noncovalent interactions for their recognition process. This dynamic behavior allows host-guest chemistry to be employed for various state of the art applications. Herein, we demonstrate the use of the dynamic supramolecular interaction to enable nanoscopic imaging inside cells and tissues. This imaging method exploits repetitive and transient binding of fluorescently labeled hexamethylenediamine (HMD) guest molecule to complementary cucurbit[7]uril (CB[7]) host to obtain stochastic switching between fluorescence ON- and OFF-states. Through connecting CB[7] hosts to targeting ligands (e.g., antibodies and small molecules), we show that this autonomous blinking enables two-dimensional (2D) and 3D super-resolution imaging of proteins in fixed cells and tissues. Finally, we exploited the capability of host-guest molecules to maintain their interaction specificity in the complexity of the live intracellular environment to obtain super-resolution actin imaging in living HeLa cell.

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